693.932 PEOPLE
| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Pierce, Stephen
University of Strathclyde
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (51/51 displayed)
- 20243-Dimensional residual neural architecture search for ultrasonic defect detectioncitations
- 2023Flexible and automated robotic multi-pass arc welding
- 2023Application of eddy currents for inspection of carbon fibre composites
- 2023Application of machine learning techniques for defect detection, localisation, and sizing in ultrasonic testing of carbon fibre reinforced polymers
- 2023In-process non-destructive evaluation of metal additive manufactured components at build using ultrasound and eddy-current approachescitations
- 2023Mapping SEARCH capabilities to Spirit AeroSystems NDE and automation demand for composites
- 2023Using neural architecture search to discover a convolutional neural network to detect defects From volumetric ultrasonic testing data of composites
- 2023Phased array inspection of narrow-gap weld LOSWF defects for in-process weld inspection
- 2023Driving towards flexible and automated robotic multi-pass arc welding
- 2022Transfer learning for classification of experimental ultrasonic non-destructive testing images from synthetic data
- 2022Mechanical stress measurement using phased array ultrasonic system
- 2022Towards ultrasound-driven, in-process monitoring & control of GTA welding of multi-pass welds for defect detection & prevention
- 2022Automated bounding box annotation for NDT ultrasound defect detection
- 2022Multi-sensor electromagnetic inspection feasibility for aerospace composites surface defects
- 2022Investigating ultrasound wave propagation through the coupling medium and non-flat surface of wire + arc additive manufactured components inspected by a PAUT roller-probe
- 2022Automated multi-modal in-process non-destructive evaluation of wire + arc additive manufacturing
- 2022Towards real-time ultrasound driven inspection and control of GTA welding processes for high-value manufacturing
- 2022Dual-tandem phased array inspection for imaging near-vertical defects in narrow gap welds
- 2022In-process non-destructive evaluation of wire + arc additive manufacture components using ultrasound high-temperature dry-coupled roller-probe
- 2022Automated real time eddy current array inspection of nuclear assetscitations
- 2021Feed forward control of welding process parameters through on-line ultrasonic thickness measurementcitations
- 2021A cost-function driven adaptive welding framework for multi-pass robotic weldingcitations
- 2021Non-contact in-process ultrasonic screening of thin fusion welded jointscitations
- 2020In-process calibration of a non-destructive testing system used for in-process inspection of multi-pass weldingcitations
- 2020Machine learning at the interface of structural health monitoring and non-destructive evaluationcitations
- 2020Quantifying impacts on remote photogrammetric inspection using unmanned aerial vehiclescitations
- 2020Laser-assisted surface adaptive ultrasound (SAUL) inspection of samples with complex surface profiles using a phased array roller-probe
- 2019Ultrasonic phased array inspection of wire + arc additive manufacture samples using conventional and total focusing method imaging approachescitations
- 2019Electromagnetic acoustic transducers for guided-wave based robotic inspection
- 2019A probabilistic compressive sensing framework with applications to ultrasound signal processingcitations
- 2019Ultrasonic phased array inspection of a Wire + Arc Additive Manufactured (WAAM) sample with intentionally embedded defectscitations
- 2019Towards guided wave robotic NDT inspection
- 2018Machining-based coverage path planning for automated structural inspectioncitations
- 2018Ultrasonic phased array inspection of wire plus arc additive manufacture (WAAM) samples using conventional and total focusing method (TFM) imaging approaches
- 2016Investigation of synthetic aperture methods in ultrasound surface imaging using elementary surface typescitations
- 2016Robotic ultrasonic testing of AGR fuel claddingcitations
- 2016Conformable eddy current array deliverycitations
- 2016Robotic path planning for non-destructive testing - a custom MATLAB toolbox approachcitations
- 2014Automatic ultrasonic robotic arraycitations
- 2014Robotic path planning for non-destructive testing of complex shaped surfaces
- 2013The feasibility of synthetic aperture guided wave imaging to a mobile sensor platformcitations
- 2012Features for damage detection with insensitivity to environmental and operational variationscitations
- 2011Some experimental observations on the detection of composite damage using lamb wavescitations
- 2011On impact damage detection and quantification for CFRP laminatescitations
- 2010A comparison of methods used to predict the vibrational energy required for a reliable thermosonic inspection
- 2010Monitoring crack propagation in turbine blades caused by thermosonic inspection
- 2008Damage localisation in a stiffened composite panelcitations
- 2007Damage detection using stress waves and multivariate statistics, an experimental case study of an aircraft componentcitations
- 2007Damage location in a stiffened composite panel using Lamb waves and neural networks
- 2006On the reproducibility of transducer coupling for acoustic emission testing
- 2001On the long-term stability of normal condition for damage detection in a composite panel
Places of action
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article
Machine learning at the interface of structural health monitoring and non-destructive evaluation
Abstract
While both non-destructive evaluation (NDE) and structural health monitoring (SHM) share the objective of damage detection and identification in structures, they are distinct in many respects. This paper will discuss the differences and commonalities and consider ultrasonic/guided-wave inspection as a technology at the interface of the two methodologies. It will discuss how data-based/machine learning analysis provides a powerful approach to ultrasonic NDE/SHM in terms of the available algorithms, and more generally, how different techniques can accommodate the very substantial quantities of data that are provided by modern monitoring campaigns. Several machine learning methods will be illustrated using case studies of composite structure monitoring and will consider the challenges of high-dimensional feature data available from sensing technologies like autonomous robotic ultrasonic inspection.